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create_character_from_description

Invent a new character from a text description and generate its portrait — the full "make me a character, no photo involved" path in ONE call, instead of gluing together create_character + update_character + generate_character_image yourself.

name: short and unique among YOUR OWN characters (see list_characters()) — how
you'll refer to this character afterwards, e.g. character="detective_marlowe" in
generate_with_face.
description: physical description — build, hair, eyes, clothing, distinguishing
features. Saved on the character's card AND used to generate the portrait, so
write it as concretely as you would any image prompt.
account: farm account (and its project) to create the character under.

The portrait is written to Flow's card exactly ONCE — that slot cannot be
regenerated. Calling this again with the SAME name does not retry it: it fails
fast with a clear message instead of hitting a raw HTTP 500 downstream. Want a
different look? Use a new name.

Returns {"name", "entity_id", "portrait_media_id", "portrait_url", "hint"} once
done. Next step for ANY further image of this character: generate_with_face(
character=name, prompt="...") — never entity_id/character_slot_index, which only
works for that one portrait write and cannot place the character into new scenes.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
nameYes
modelNoNARWHAL
aspectNoIMAGE_ASPECT_RATIO_PORTRAIT
accountYes
descriptionYes
display_nameNo
portrait_promptNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.9/5.0
Behavior5/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

The description adds important behavioral context beyond the annotations: the portrait slot is written only once and cannot be regenerated, calling with the same name fails fast rather than retrying, and the return shape is stated. This materially changes how an agent should plan calls and handle errors.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is long but well-structured and front-loaded: purpose first, then parameter semantics, then behavioral caveats, then return and follow-up. Every sentence adds practical information; there is no filler or restatement of the tool name.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex creation tool with no output schema and no param descriptions, this description is unusually complete: it explains the one-shot portrait behavior, return fields, naming constraints, and the correct next-step tool. An agent has enough context to invoke it correctly and avoid the common misuse of entity_id-based image generation.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

With 0% schema description coverage, the description carries the parameter burden and does a strong job on the three required parameters: name uniqueness, description-as-image-prompt guidance, and account ownership. It leaves optional parameters like display_name and portrait_prompt mostly implicit, but their titles/enums/defaults convey most of their meaning.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description opens with a clear verb and resource: 'Invent a new character from a text description and generate its portrait.' It also differentiates itself from the photo-based sibling and from manually chaining create_character + update_character + generate_character_image, so an agent can immediately tell which tool matches the 'no photo involved' path.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines5/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It explicitly says this tool replaces the multi-step composition, references list_characters() as a prerequisite for choosing a unique name, and directs the agent to generate_with_face for any future image of the character. It also warns against using entity_id/character_slot_index for new scenes, giving clear routing beyond the call itself.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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